Publications by authors named "Patricia Deverka"

Germline genetic testing for inherited cancer risk has shifted to multi-gene panel tests (MGPTs). While MGPTs detect more pathogenic variants, they also detect more variants of uncertain significance (VUSs) that increase the possibility of harms such as unnecessary surgery. Data sharing by laboratories is critical to addressing the VUS problem.

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The National Center for Advancing Translational Sciences' virtual 2021 conference on gene-targeted therapies (GTTs) encouraged multidisciplinary dialogue on a wide range of GTT topic areas. Each of three parallel working groups included social scientists and clinical scientists, and the three major sessions included a presentation on economic issues related to their focus area. These experts also coordinated their efforts across the three groups.

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Objective: The Genomic Medicine Working Group of the National Advisory Council for Human Genome Research virtually hosted its 13th genomic medicine meeting titled "Developing a Clinical Genomic Informatics Research Agenda". The meeting's goal was to articulate a research strategy to develop Genomics-based Clinical Informatics Tools and Resources (GCIT) to improve the detection, treatment, and reporting of genetic disorders in clinical settings.

Materials And Methods: Experts from government agencies, the private sector, and academia in genomic medicine and clinical informatics were invited to address the meeting's goals.

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There is a tremendous public health need to identify potentially lethal cancers at earlier stages, when there is a greater chance for improved survival. Although in the US there are currently screening recommendations for only five cancers (breast, colorectal, cervical, lung, and prostate), new tests can screen for up to fifty cancers simultaneously based on a simple blood draw. However, these multicancer screening tests (also called "liquid biopsy" tests) will also present challenges to payers because of intrinsic features of the tests and the complexity of payer coverage assessments for screening tests.

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Purpose: To evaluate mammography uptake and subsequent breast cancer diagnoses, as well as the prospect of additive cancer detection a liquid biopsy multi-cancer early detection (MCED) screening test during a routine preventive care exam (PCE).

Methods: Patients with incident breast cancer were identified from five years of longitudinal Blue Health Intelligence (BHI) claims data (2014-19) and their screening mammogram and PCE utilization were characterized. Ordinal logistic regression analyses were performed to identify the association of a biennial screening mammogram with stage at diagnosis.

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Background: Employer-sponsored corporate wellness programs have spread despite limited evidence of effectiveness in improving health or reducing costs. Some programs have offered genetic testing as a benefit to employees, but little is known about this practice.

Methods: In December 2019, we conducted a systematic Google search to identify vendors offering corporate wellness programs involving genetics.

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Objectives: Given the potential of real-world evidence (RWE) to inform understanding of the risk-benefit profile of next-generation sequencing (NGS)-based testing, we undertook a study to describe the current landscape of whether and how payers use RWE as part of their coverage decision making and potential solutions for overcoming barriers.

Methods: We performed a scoping literature review of existing RWE evidentiary frameworks for evaluating new technologies and identified barriers to clinical integration and evidence gaps for NGS. We synthesized findings as potential solutions for improving the relevance and utility of RWE for payer decision-making.

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Advances in technologies for assessing genomic variation and an increasing understanding of the effects of genomic variants on health and disease are driving the transition of genomics from the research laboratory into clinical care. Genomic medicine, or the use of an individual's genomic information as part of their clinical care, is increasingly gaining acceptance in routine practice, including in assessing disease risk in individuals and their families, diagnosing rare and undiagnosed diseases, and improving drug safety and efficacy. We describe the major types and measurement tools of genomic variation that are currently of clinical importance, review approaches to interpreting genomic sequence variants, identify publicly available tools and resources for genomic test interpretation, and discuss several key barriers in using genomic information in routine clinical practice.

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Meaningful participant engagement has been identified as a key contributor to the success of efforts to share data via a "Medical Information Commons" (MIC). We present findings from expert stakeholder interviews aimed at understanding barriers to engagement and the appropriate role of MIC participants. Although most interviewees supported engagement, they distinguished between individual versus collective forms.

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A medical information commons (MIC) is a networked data environment utilized for research and clinical applications. At three deliberations across the U.S.

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Advances in technologies and biomedical informatics have expanded capacity to generate and share biomedical data. With a lens on genomic data, we present a typology characterizing the data-sharing landscape in biomedical research to advance understanding of the key stakeholders and existing data-sharing practices. The typology highlights the diversity of data-sharing efforts and facilitators and reveals how novel data-sharing efforts are challenging existing norms regarding the role of individuals whom the data describe.

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Drawing on a landscape analysis of existing data-sharing initiatives, in-depth interviews with expert stakeholders, and public deliberations with community advisory panels across the U.S., we describe features of the evolving medical information commons (MIC).

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Background: Clinical use of next-generation sequencing (NGS) tests has been increasing, but few studies have examined their economic value. Several studies have noted that there are methodological challenges to conducting economic evaluations of NGS tests.

Objective: Our objective was to examine key methodological challenges for conducting economic evaluations of NGS tests, prioritize these challenges for future research, and identify how studies have attempted solutions to address these challenges.

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Genetic testing and spending on that testing have grown rapidly since the mapping of the human genome in 2003. However, it is not widely known how many tests there are, how they are used, and how they are paid for. Little evidence from large data sets about their use has emerged.

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For the past two decades, the National Cancer Institute (NCI) has supported the involvement of patient advocates in both internal advisory activities and funded research projects to provide a patient perspective. Implementation of the inclusion of patient advocates has varied considerably, with inconsistent involvement of patient advocates in key phases of research such as concept development. Despite this, there is agreement that patient advocates have improved the patient focus of many cancer research studies.

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Response to a drug often differs widely among individual patients. This variability is frequently observed not only with respect to effective responses but also with adverse drug reactions. Matching patients to the drugs that are most likely to be effective and least likely to cause harm is the goal of effective therapeutics.

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Objectives: The aim of this study was to examine the evidence payers cited in their coverage policies for multi-gene panels and sequencing tests (panels), and to compare these findings with the evidence payers cited in their coverage policies for other types of medical interventions.

Methods: We used the University of California at San Francisco TRANSPERS Payer Coverage Registry to identify coverage policies for panels issued by five of the largest US private payers. We reviewed each policy and categorized the evidence cited within as: clinical studies, systematic reviews, technology assessments, cost-effectiveness analyses (CEAs), budget impact studies, and clinical guidelines.

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